There are applications in which a distance measurement is needed for a plurality of locations in the environment surrounding a distance measurement system. There are existing technologies that provide such distance information in the form of a 3-dimensional (3D) point cloud that represents the 3D coordinates of points on objects in the local environment. An ongoing challenge is to enhance these distance measurement systems, for example to provide improved coverage range, measurement density, measurement accuracy, measurement relevance. One challenge is that most cases real-world applications of distance measurement (e.g. ranging in autonomous vehicles) can encounter obstacles that dynamically obstruct portions of the field of view (FOV). For example, the trailer of a tractor-trailer truck can obstruct a dynamically varying portion of the FOV of a distance measurement system located in the tractor portion of the truck.
One exemplary distance measurement technology is computer stereo vision in which 3D information is extracted from 2-dimensional (2D) images obtained by a digital camera, by comparing captured information about the scene from two vantage points. Another exemplary distance measurement technology is light detection and ranging (LIDAR) in which a light emitter (e.g. a laser diode) illuminates one or more directions in a field of view and the time associated with the reflections from each of the one or more directions is used to measure distance to objects in the associated direction. Several varieties of LIDAR are presently used. For example, flash LIDAR illuminates many points at once with light in a FOV and uses an array of detectors to sense reflections and associated times. Scanned LIDAR can use a pulsed laser to scan the FOV and sequentially measure laser reflections.
Another challenge with LIDAR is that the FOV represents the limited set of directions in which the LIDAR can directly measure distance to surrounding locations. Conventional mechanical LIDAR can have a rotating sensor head that spins around an axis and provides a 360 degree FOV in the azimuthal plane and a limited (e.g. +/−20 degree) FOV in the elevation plane. Hence the directions in which a LIDAR can provide direct range measurements from the surrounding environment can be limited by the system design. In a related challenge the LIDAR is often mounted on a platform (e.g. a car, truck, or airplane) and this platform obstructs some of the FOV. Therefore insofar as I am aware, no previous LIDAR system effectively addresses the challenge of adapting the limited FOV to the often-obstructed and changing local environment in real-world applications (e.g. autonomous vehicles or smart buildings).